With the widespread use of portable terminals and tablet PCs and the rapid expansion of mobile computing based on wireless Internet technology, a dramatic increase in a wireless network capacity is required.
In many studies, it is predicted that traffic usage of mobile users will increase rapidly in the future. As a representative solution to meet the requirements according to such explosive traffic growth, a method that applies an evolved physical layer technique or allocates an additional spectrum may be considered. However, the physical layer technology reaches a theoretical limit, and increasing a capacity of a cellular network through the allocation of the additional spectrum cannot be a fundamental solution.
Accordingly, as a method for efficiently supporting user data traffic that explosively increases in the cellular network, a method of providing a service by densely installing more small cells with a smaller size by reducing the size of a cell can be considered as a practical alternative.
Meanwhile, proposed is cognitive radio technology which is frequency sharing technology in which by measuring a propagation environment so that different types of wireless communication services can use the same frequency, a user who is granted permission to use a frequency in the related art can search for an idle frequency that is not being used and performs communication at the frequency.
Appropriate resource allocation should be performed to protect the macro base station in a cognitive small cell network (CSN) that incorporates the cognitive radio communication technology in such a small cell network and to guarantee the minimum data transmission rate requirement of a cognitive small cell user.
However, in the case of uplink transmission in the cognitive small cell network, a resource allocation condition for maximizing the total data transmission rate during uplink data transmission while protecting a macro base station and guaranteeing the minimum data transmission rate requirement of the cognitive small cell user is difficult to optimize due to an NP-hard problem.